Enhancement of Hounsfield unit distribution in cone-beam CT images for adaptive radiation therapy: Evaluation of a hybrid correction approach

Abstract

PurposeThis study aims to evaluate the accuracy of a hybrid approach combining the histogram matching (HM) and the multilevel threshold (MLT) to correct the Hounsfield Unit (HU) distribution in cone-beam CT (CBCT) images. Methods and MaterialsCBCT images acquired for ten prostate cancer patients were processed by matching their histograms to those of deformed planning CT (pCT) images obtained after applying a deformable registration (DR) process. Then, HU values corresponding to five tissue types in the pCT were assigned to the obtained CBCT images (CBCTHM-MLT). Finally, the CBCTHM-MLT images were compared to the deformed pCT visually and using different statistical metrics. ResultsThe visual assessment and the profiles comparison showed that the high discrepancies in the CBCT images were significantly reduced when using the proposed approach. Furthermore, the correlation values indicated that the CBCTHM-MLT were in good agreement with the deformed pCT with correlation values ranging from 0.9893 to 0.9962. In addition, the root mean squared error (RMSE) over the entire volume was reduced from 64.15 ± 9.50 to 51.20 ± 6.76 HU. Similarly, the mean absolute error in specific tissue classes was significantly reduced especially in the soft tissue-air interfaces. These results confirmed that applying MLT after HM worked better than using only HM for which the correlation values were ranging from 0.9878 to 0.9955 and the RMSE was 55.95 ± 10.43 HU. ConclusionEvaluation of the proposed approach showed that the HM + MLT correction can improve the HU distribution in the CBCT images and generate corrected images in good agreement with the pCT.